Gordon Logan
Vanderbilt University
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Primary Section: 52, Psychological and Cognitive Sciences Membership Type:
International Member
(elected 2019)
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Biosketch
Gordon Logan is a cognitive psychologist known for his work on attention, skill acquisition, and cognitive control. He is particularly known for his instance theory of automatization, which describes learning as the accumulation of specific memories, and for his work on response inhibition and the stop signal task, which is widely used in cognitive neuroscience and studies of psychological and neurological disorders. His recent work has focused on multitasking and control of skilled performance (typewriting) and grounding computational models of decision making in the activity of individual neurons in visual search and stop signal tasks. Logan was born in Edmonton, Alberta, Canada and grew up in Dawson Creek, British Columbia, Canada. He received his B.A. and M.Sc. from University of Alberta and his Ph.D. from McGill University. He worked Queen’s University, University of Waterloo, University of Toronto, and University of British Columbia in Canada before moving to Purdue University, University of Illinois, and Vanderbilt University. He is a Centennial Professor of Psychology and a fellow of the Society of Experimental Psychologists and the Psychonomic Society and he is a member of the American Academy of Arts and Sciences.
Research Interests
Gordon Logan's research focuses on attention, skill acquisition, and cognitive control, combining experiments with computational modeling. His work on attention addresses how attention can be cued externally to locations in the visual field and cued internally to select among ways to analyze perceptual input. He addresses conflict tasks, providing an early theory of the Stroop task and discovering the effect of manipulating the likelihood of conflict. Logan’s main contribution to skill acquisition is the "instance theory of automatization," in which performers remember solutions to problems they encounter and retrieve prior solutions when problems repeat, instead of solving the problem all over again. This theory generalizes the law of practice from mean response times to entire distributions of response time and motivates experiments on the role of attention in learning and accessing learned knowledge. Logan’s main contribution to cognitive control has been empirical and theoretical accounts of response inhibition in the stop signal task, where people are required to stop a response they are executing. His theory explains response inhibition as a race between "stop" and "go" processes and provides a measure of the latency of the stop process, which produces no overt response.
More recently, he has provided critical theory and data on multitasking and executing highly practiced skills (typing). He developed and tested theories that relate computational models of decision making to individual neurons that implement decisions in monkeys.
